Inspection data analyzing system

ABSTRACT

The present invention provides data analysis stations respectively for a probing tester and an automatic particle inspection machine. And, in the data analysis station, the coordinates on which the disposition of the chips are described on a product basis are equal to those on which the locations of the defects are described. Further, the station provides a function of determining which of the chips each defect belongs to. These data analysis stations are connected through a communication line. The present invention is capable of analyzing the data on a chip basis, resulting in being able to grasp the relation between how the defects are caused on each chip and the product character of the chip.

BACKGROUND OF THE INVENTION

[0001] The present invention concerns visual inspection for a product ora part being manufactured and more particularly to an inspection dataanalyzing system which is capable of inspecting defects or particles ona surface of the product or part and analyzing the inspection data.

[0002] In the manufacture of a semiconductor device or the like, productdefects often result from particles or other defects existing on asurface of a work piece (noting that particles are one type of defectthat can occur). It is, therefore, necessary to quantitatively inspectparticles or other defects for normally monitoring if a problem occursin the manufacturing machine or the environment around it. And, it isnecessary to grasp how the particles or other defects have an adverseeffect on yield and take effective measures for the particles or otherdefects for improving the yield. Hereinafter, the terms “particles orother defects” will sometimes be generally referred to as “defects”, butwhen specific reference is made only to particles, it will be identifiedas such.

[0003] As an example, the use of an automatic visual inspection machinefor data analysis in the manufacture of semiconductors has beendisclosed in an article entitled “How does the automatic waferinspection improve a yield?”, Solid State Technology (Japanese Version),July 1988, pages 44 to 48. The visual inspection is carried out forwafers in more than one manufacturing process. Hence, the inspectiondata includes data for managing the inspection data itself. The managingdata contains a product name of a inspected wafer, a lot number, a wafernumber, and an inspected process, data, and time, for example. It isnecessary to analyze not only the inspection data but also the managingdata. The conventional visual inspection machine includes a function ofmeasuring sizes of defects and where the defects are located on a wafercoordinate, a function of measuring the number of defects existing on awafer, and a means for allowing an operator to determine a category ofdefects, and the like. The machine inspects the change of the number ofdefects on each wafer, the distribution of defect frequency on awafer-size basis, and the like. Further, the machine serves to analyzethe correlation between the number of defects on each wafer (defectsdensity) and the yield of the wafer as well.

[0004] And, each wafer has to be identified in more than one visualinspection process in the data analysis. Conventionally, the operatorhas visually recognized a wafer number. To reduce the burden of thisoperation, an automatic particle inspection machine having a means forautomatic recognition of a wafer number has been disclosed inJP-A-63-213352.

[0005] Known automatic visual inspection machines have been categorizedinto two groups. One is referred to as an automatic particle inspectionmachine which is an inspection machine employing a light-scatteringsystem. This machine serves to inspect particles existing on a wafer. Itis thus unable to always inspect defects other than particles. The othergroup is an inspection machine employing a pattern recognition system.It is referred to as an automatic visual inspection machine or anautomatic defect inspection machine, which has a function of accuratelyrecognizing other defects in addition to particles. The automatic visualinspection machine needs an inspection time which is about 1000 times aslong as the time required by the automatic particle inspection machine.The former machine can thus inspect a far smaller number of wafers thanthe latter. For monitoring how defects are caused in a mass productionline, two methods are provided. The first method is to restrict theprocesses to be visually inspected to a specific process (Solid StateTechnology (Japanese Version), July 1988, pages 44 to 48). The secondmethod is to take the steps of matching the particle inspection data tothe visual inspection data over all the processes and machines, checkingthe correlation between particles and defects, and presuming how defectsare caused on the particle inspection data (Semiconductor World, May1989, pages 118 to 125). Further, in analyzing data, these methodsrequire an operator who serves to analyze data, because there exist alot of data and various kinds of data analysis methods in analyzingdata.

[0006] The conventional method is uncapable of grasping how defects arecaused on each chip. Hence, they can merely perform correlation analysisbetween the number of defects per wafer and a yield. That is, thesemethods have a disadvantage that they cannot grasp the relation betweendefects per wafer and a product character. In addition, onesemiconductor for one wafer is provided at this time, while two or moresemiconductors for one wafer will be provided in future. It is necessaryto enhance the data processing unit from a wafer unit to a chip-unitbasis. A new data analysis technique is expected accordingly.

[0007] And, for inspecting how many defects are caused in a massproduction line, the foregoing first method is designed to determine theprocess to be visually inspected on the basis of the knowledge of anoperator and the result of a probing test. The foregoing second methodrequires large labor for matching the particle inspection data to thevisual inspection data over all the processes and machines.

[0008] Moreover, an operator who is mainly in charge of maintaining andmanaging the manufacturing machine does not have spare time to analyzethe inspection data of a wafer given by his or her machine. Hence, theoperator requests the data analysis of another operator who is mainly incharge of it. However, novel data analysis method and means are expectedwhich anyone can operate easily and quickly and which serve to outputthe analyzed data.

SUMMARY OF THE INVENTION

[0009] It is therefore an object of the present invention to provide aninspection data analysis system which is capable of analyzing data perchip for the purpose of grasping the relation between the occurrencecondition of defects per chip and the product character of each chip.

[0010] And, it is a further object of the present invention to providean inspection data analyzing system which is capable of easilydetermining a manufacturing process which causes problems and thecontents or the problems.

[0011] It is another object of the present invention to provide aninspection data analyzing system which is capable of monitoring theoverall production line and efficiently inspecting the quantity ofcaused defects in a mass production line.

[0012] To achieve the foregoing objects, the present invention offers aprobing tester, an automatic particle inspection machine, and anautomatic visual inspection machine respectively having data analysisstations. Each data analysis station has chip arrangement informationfor each product and serves to describe the locations of defects on thecoordinate system on which the chip disposition is described. And, thestation provides a function for determining on which chip each defect iscaused. These data analysis stations are linked with a communicationline.

[0013] Further, for inspecting the quantity of caused defects in themass production line, the particle inspection machine operated at ahigher inspection speed employs the step of monitoring the overallmanufacturing line, inspecting the portions around caused defects, andmonitoring the quantity of caused defects.

[0014] And, in order for anyone to use the machine, the data analysisstation is designed to offer a routine data retrieval method, a routineoperation method, and a routine analysis result output format.

[0015] As mentioned above, each data analysis station provides chipdisposition information, a function of describing the locations ofcaused defects on the coordinate system on which the chip disposition isdescribed, and a function of determining on which chip each defect iscaused. It is thus possible to grasp how particles are attached anddefects are caused on each chip. By linking these data analysis stationswith a communication line, therefore, the data analysis station forprcbing test data sends the probing data to the station for particlesand defects data so that the latter station can inspect the relationbetween the condition of caused defects on each chip and the probingtest result (product character). As will be understood from the abovedescription, the present invention is designed so that the particleinspection machine operating at a higher inspection speed serves tomonitor the overall manufacturing line and the visual inspection machineserves to inspect portions around caused particles for inspecting thequantity of caused defects. Hence, this invention is capable ofefficiently inspecting the quantity of caused defects in a massproduction line.

[0016] Further, in analyzing data, as mentioned above, this inventionhas a routine data retrieval method, a routine operating method, and aroutine output format, so that anyone can analyze the data and obtainclear outputs.

BRIEF DESCRIPTION OF THE DRAWINGS

[0017]FIG. 1 is a diagram showing overall arrangement of an inspectiondata analysis system according to an embodiment of the presentinvention;

[0018]FIG. 2 is a diagram showing partial arrangement of a particleinspection system shown in FIG. 1;

[0019]FIG. 3 is a diagram showing arrangement of a particle inspectionmachine shown in FIG. 2;

[0020]FIG. 4 is a diagram showing a particle data analysis station shownin FIG. 2;

[0021]FIG. 5A is a chart showing a data table for each lot in a particledatabase;

[0022]FIG. 5B is a chart showing a data table for each wafer in theparticle database;

[0023]FIG. 5C is a chart showing a data table for each particle in theparticle database;

[0024]FIG. 6 is a view showing how to set a particle coordinate system;

[0025]FIG. 7 is a chart showing arrangement of a map information filefor each product;

[0026]FIG. 8 is a chart showing arrangement of a lot number managingfile for each product;

[0027]FIG. 9 is a flowchart showing the procedure involved withregistration of data;

[0028]FIG. 10 is a flowchart showing the procedure involved withdeletion of data;

[0029]FIG. 11 is a view showing an initial screen;

[0030]FIG. 12 is a view showing a retrieval screen;

[0031] FIGS. 13 to 18 are views respectively showing a list of eachdata;

[0032]FIG. 19 is a view showing an analysis screen;

[0033]FIG. 20 is a view showing a particle map, used for analyzing thedistribution of particles;

[0034]FIG. 21 is a view showing a map about how particles are attachedon chips, used for analyzing the distribution of particles;

[0035]FIG. 22 is a flowchart showing an algorithm for determining whichchip particles are attached;

[0036]FIG. 23 is a view showing a screen output in case of optionallydividing a wafer, used for analyzing the distribution of particles;

[0037]FIG. 24 is a view showing how a wafer is divided, using foranalyzing the distribution of particles;

[0038]FIG. 25 is a chart showing a map information file;

[0039]FIG. 26 is a chart showing a particle density to divided locationsof the wafer, used for analyzing the distribution of particles;

[0040]FIG. 27 is a view showing a pattern on which the wafer is divided;

[0041]FIG. 28 is a chart showing how particles are distributed in awafer;

[0042]FIG. 29 is a chart showing a particle trend, used for monitoringthe amount of particles in number;

[0043]FIG. 30 is a chart showing frequency distributions of particlenumber in inspection periods and an average trend in each period, usedfor monitoring the amount of particles in number;

[0044]FIG. 31 is a chart showing how the particle number is changed ineach sample process, used for monitoring the amount of particles innumber;

[0045]FIG. 32 is a chart showing the particle hysteresis, whichinformation is used for finding a critical process;

[0046]FIG. 33 is a flowchart showing an algorithm for particle trace;

[0047]FIG. 34 is a chart showing a format containing an inspectedparticle list and an existing particle list;

[0048]FIG. 35 is a view showing partial arrangement of the visualinspection system shown in FIG. 1;

[0049]FIG. 36 is a view showing arrangement of the visual inspectionmachine shown in FIG. 35;

[0050]FIG. 37 is a view showing arrangement of the defects data analysisstation shown in FIG. 35;

[0051]FIG. 38A is a chart showing a data table for each lot in thedefects database shown in FIG. 37;

[0052]FIG. 38B is a chart showing a data table for each wafer in thedefects database shown in FIG. 37;

[0053]FIG. 38C is a chart showing a data table for each defect in thedefects database shown in FIG. 37;

[0054]FIG. 39 is a chart showing a wafer number management file for eachproduct;

[0055]FIG. 40 is a chart showing how a chip fraction defective ischanged;

[0056]FIG. 41 is a chart showing how a chip defects density is changed;

[0057]FIG. 42 is a chart showing a fraction defective in each sampleprocess;

[0058]FIG. 43 is a chart showing another fraction defective in eachsample process;

[0059]FIG. 44 is a diagram showing a particle inspection machine, aparticle data analysis station, a probing tester, and a probing testdata analysis station, which correspond to partial arrangement of thesystem shown in FIG. 1;

[0060]FIG. 45 is a diagram showing arrangement of the probing tester;

[0061]FIG. 46 is a diagram showing arrangement of the probing dataanalysis station;

[0062]FIG. 47 is a diagram showing arrangement of the particle dataanalysis station;

[0063]FIG. 48A is a chart showing a probing test lot data table in aprobing test database shown in FIG. 46;

[0064]FIG. 48B is a chart showing a probing test wafer data table in theprobing test database shown in FIG. 46;

[0065]FIG. 49 is a chart showing an analysis data auxiliary file;

[0066]FIG. 50 is a chart showing correlation analysis between the amountof particles in number and the yield of chips, which is used for settinga reference value for management of the analysis process;

[0067]FIG. 51 is a flowchart for deriving correlation between theparticle number and the yield;

[0068]FIG. 52 is a chart showing an overlay trend between the particlenumber and the yield;

[0069]FIG. 53 is a chart showing a yield for each particle diametersize;

[0070]FIG. 54 is a chart showing a fraction defective in each sampleprocesses;

[0071]FIG. 55 is a diagram showing a visual inspection machine, which ispart of the system shown in FIG. 1;

[0072]FIG. 56 is a diagram showing arrangement of a defects dataanalysis station;

[0073]FIG. 57 is a diagram showing a relation between a particleinspection process and a visual inspection process;

[0074]FIG. 58 is a diagram showing an overall system according toanother embodiment of the present invention;

[0075]FIG. 59 is a diagram showing a data analysis station included inthe system shown in FIG. 58;

[0076]FIG. 60 is a view showing how to set a coordinate system when amagnetic disk is to be inspected; and

[0077]FIG. 61 is a view showing how to set a coordinate system when acircuit substrate is to be inspected.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0078] The overall arrangement of the system will be described withreference to FIG. 1. This embodiment is a manufacturing line forsemiconductor devices to which the present invention is applied. Thereference numeral 12 denotes a semiconductor device manufacturingprocess. It is normally located in a clean room 13 in which theenvironment is kept clean. In the clean room 13, there are provided aparticle inspection machine 1 having a function of measuring the numberof defects existing on a product wafer and the locations of the defectson a wafer coordinate system, a visual inspection machine 4 havingfunctions of measuring the number of defects existing on a product waferand the locations of the defects on the wafer coordinate system and ofrecognizing a category of defects (the visual inspection machine 4simply referred hereinafter indicates this inspection machine. Thisinspection machine serves to inspect general defects such as patterndefects, particles, and discoloration defects.), and a probing tester 7for testing the product character of a chip. These machines aredisclosed in Kubota et. al.; “Particle and Visual Inspection Machines”Hitachi Critique, 71 volumes, No. 5, pages 55 to 62, for example. Theparticle inspection machine 1, the visual inspection machine 4, and theprobing tester 7 respectively provide a particle data analysis station2, a defects data analysis station 5, and a probing test data analysisstation 8, which are all installed outside of the clean room 13. Theinspection machines 1, 4, 7 are linked with the analysis stations 2, 5,8 through communication lines 3, 6, 9. Further, the particle analysisstation 2 is linked with the probing test data analysis station 8through a communication line 10 and the defects analysis station 5 islinked with the probing test data analysis station 8 through acommunication line 11.

[0079] On the semiconductor device manufacturing line, wafers aretransported in lots. For particle- or visual-inspecting these wafers,after finishing the process to be particle- or visual-inspected, eachlot is carried to the particle inspection machine 1 or the visualinspection machine 4 in which some or all wafers contained in the lotare inspected. For carrying out the particle or visual inspection, it ispossible to employ a method for determining a subject process on thebasis of the operator's knowledge or a method for determining a processto be visually inspected on the basis of the particle-inspecting resultas mentioned below. In the particle or visual inspection, data issupplied to each inspection machine. The data contains a lot number of awafer, a wafer number, an inspection day and time, a process locatedimmediately before the inspection, and the like. The process-completedwafers are carried to the probing tester 7 at each lot, in which tester7 all the wafers contained in the lot are subject to a probing test.Herein, the lot number of a wafer, the wafer number, and the inspectionday and time are supplied to the probing tester 7. The particle dataanalysis station 2 and the defects data analysis station 5 containinformation about how chips are disposed on a wafer for each product.Based on the information, these stations serve to determine which chipthe inspected defects belong to on the basis of the locations of theinspected defects placed on the chip coordinate system and count howmany defects are brought about on each chip. Based on the number ofdefects existing on a wafer, the location coordinates of the defects,and the number of defects on a chip, the particle inspection dataanalysis station 2 and the visual inspection data analysis station 5serve to carry out the analysis described hereinafter. Further, theparticle inspection data analysis station 2 and the visual inspectiondata analysis station 5 serve to carry out the analysis describedhereinafter on the basis of the number of defects existing on a wafer,the location coordinates of defects, the number of defects on a chip,and the data about a product character read from the probing test dataanalysis station 8.

[0080] Next, referring to FIG. 2, there will be described an arrangementof the particle inspection machine 1 and the particle inspection dataanalysis station 2 included in the inspection data analysis system ofFIG. 1.

[0081] The present system consists of the particle inspection machine 1for inspecting particles on a wafer and the particle data analysisstation 2 for analyzing data sent from the particle inspection machine1. The former machine 1 is connected to the latter station 2 with acommunication line 3.

[0082]FIG. 3 illustrates the arrangement of the particle inspectionmachine 1. The particle inspection machine 1 comprises a particle sensor1001, a particle sensing signal processing unit 1002, a memory 1003, akeyboard 1004 served as an input unit, a bar-code reader 1005, a CRT1006 and a printer 1007, both of which are served as an output unit, andan external communication unit 1008 for carrying out the communicationwith the particle data analysis station 2. The machine 1 has a functionof defining the two-dimensional location coordinates of particles to beinspected on a wafer, the sizes of the particles, and the number ofparticles existing on the wafer.

[0083]FIG. 4 illustrates the arrangement of the particle data analysisstation 2. The particle data analysis station 2 comprises a particledata processing unit 1009, a particle database 1010 for saving theinspection data sent from the particle inspection machine 1, a keyboard1011 served as an input processing unit, a mouse 1012, a CRT 1013 and aprinter 1014 served as an output unit, an external communication unit1015 for carrying out communication with the particle inspectionmachine, a memory 1016 located inside of the particle data processingunit, an internal harddisk 1017, and a CPU 1018.

[0084] In wafer inspection, the particle management data is supplied tothe particle inspection machine 1 using the keyboard 1004 or thebar-code reader 1005. The data contains an inspected wafer name, aninspected process name, a lot number, a wafer number, inspection data,an inspection time, and an operator ID. Further, the particle inspectiondata is also saved together with the particle management data. Thisparticle inspection data contains the number of the particles existingon the inspected wafer, the location coordinates of the particles, andthe sizes of the particles, which are measured in the particleinspection machine 1. Each particle can be categorized in L, M, and Ssizes in larger order when saved.

[0085] The form of the particle database 1010 is illustrated anddescribed with reference to FIG. 5. The particle database 1010 includesthree databases referred to as a lot unit data table (see FIG. 5A), awafer unit data table (see FIG. 5B), and a particle unit data table (seeFIG. 5C). The lot unit data table serves to save particle managementdata 5001, 5002, 5003, 5005, 5006 and a wafer size 5004. The wafer unitdata table serves to save a lot number 5008, a wafer number 5009, andthe number of particles 5010 existing on the inspected wafer containedin the particle inspection data. The particle data processing unit 1009saves a map information file and a lot number management file for eachproduct in the internal harddisk 1017. The map information file containsa wafer size for each product, a chip horizontal width 1019, a chipvertical width 1020, a matrix vertical width 1022, a matrix horizontalwidth 1023, and non-use chip positions 1024, 1025 registered therein(see FIG. 6). The lot number management file for each product contains alot number 5025 for each product registered therein. The formats of themap information files will be illustrated with reference to FIG. 7. Theformat of the lot number management file for each product will beillustrated with reference to FIG. 8.

[0086] Next, how to register the data will be described with referenceto FIG. 9. After the particle inspection machine 1 finishes theinspection of one lot (step 10001), it sends the particle managementdata and the particle inspection data to the particle data analysisstation 2 through the communication line 3 (step 10002). When theparticle management data and the particle inspection data for one lotare registered in the particle database 1010 (step 10003), the particledata processing unit 1009 increments by one the lot number for eachproduct in the lot number management file for each product (step 10004).Then, the data deletion procedure is illustrated in FIG. 10. An analysisoperator routinely maintains the particle database 1010 and deletes thedata about the lot he or she determines unnecessary (step 10005). Whenthe one-lot data is deleted from the particle database 1010, theparticle data processing unit 1009 decrements by one the lot number foreach product in the lot number management file for each product (step10006). Then, in the product unit lot number management file, it isdetermined if the product unit lot number is zero (step 10007). If yes,the map information file about the product is deleted and then the fileabout the product in the product unit lot number management file isdeleted (step 10008). If no at the step 10007, the procedure is directlyfinished.

[0087] The following description concerns how to use the particle dataanalysis station 2 described with reference to FIG. 2. In the initialscreen shown in FIG. 11, several analysis function icons (1026 to 1034)are displayed. These icons include analysis functions to be describedlater. An analysis operator selects a desired analysis function icon andthen specifies a retrieval condition on a retrieval screen shown in FIG.12. For specification, one or more items are specified by the mouse 1012shown in FIG. 4 and then a finish icon 1050 is specified. This retrievalscreen comprises a basic data display column 1036 at the lower-leftportion of the screen, a database retrieval icon 1036 at the upper-leftportion, and a display section 1047 at the central to the right portion,the display section containing a product list, a process list, a lotnumber list, a wafer number list, an inspection date calendar, and anoperator name list. The basic data display column 1036 contains aproduct name 1037, a process name 1038, a lot number 1039, a wafernumber 1040, an inspection date 1041, a particle sum 1042, an L-sizedparticle number 1043, an M-sized particle number 1044, an S-sizedparticle number 1045, and an operator name 1046. For specifying theretrieval condition, it is necessary to specify the product name 1037.It is possible to specify the process name 1038, the lot number 1039,the wafer number 1040, the inspection date 1041, and the operator name1046 if necessary. The specified results are displayed on the basic datadisplay column 1036. By specifying the product name item 1037 on theinitial screen using the mouse 1012, the product name list shown in FIG.13 is displayed on the display section 1047. The displayed list includesall the product names 5001 registered in the database 1010. Further, inFIG. 13, 1048 denotes a lower scroll icon, 1049 denotes an upper scrollicon, and 1050 denotes a finish icon. When the analysis operatorspecifies one desired product name of the list with the mouse 1012, thespecified product name is displayed in the product name item 1037. Next,when the analysis operator specifies the process name in the item 1038with the mouse 1012, the process name list shown in FIG. 14 is displayedon the display section 1047. This displayed process name list containsonly the process name 5002 about the specified product names in the dataregistered in the database 1010. The analysis operator specifies adesired process name in the process name list with the mouse 1012. Then,when he or she specifies the lot number item 1039 with the mouse 1012,the lot number list is displayed as shown in FIG. 15. This lot numberlist contains only the lot number 5003 about the specified product nameand process name in the data registered in the database 1010. Theanalysis operator specifies a desired lot number from among the lotnumber list with the mouse 1012. Then, when the operator specifies thewafer number item 1040 with the mouse 1012, the wafer number list isdisplayed as shown in FIG. 16. This wafer number list contains only thewafer number 5009 about the product name 50001, the process name 5002,and the lot number 5003, which are all specified, in the data registeredin the database 1010. The analysis operator specifies a desired wafernumber from among the wafer number list with the mouse 1012. Next, whenhe or she specifies the inspection date item 1041 with the mouse 1012,an inspection date calendar is displayed as shown in FIG. 17. Theinspection date calendar indicates the earliest to the latest month ofinspection date 5005 about the product name, the process name, the lotnumber, and the wafer number, which are all specified, in the dataregistered in the database 1010. The analysis operator specifies adesired period by specifying the earlier date and the latest date in theinspection date calendar with the mouse 1012. Next, when the operatorspecifies the operator name item 1046 with the mouse 1012, the operatorname list is displayed as shown in FIG. 18. The operator name listcontains only the operator names about the product name, the processname, the lot number, the wafer number, and the inspection date, whichare all specified, in the data registered in the database 1010. Theanalysis operator specifies a desired operator name from among theoperator name list with the mouse 1012. After the desired item, ananalysis operator specifies the database retrieval icon. The particledata analysis station 2 serves to retrieve the satisfactory data aboutthe product name, the process name, the lot number, the wafer number,the inspection date, and the operator name from the particle database1010 and send it to the particle data processing unit 1009. If no itemis specified, the particle data analysis station 2 serves to retrieveall the satisfactory data about the other specified items from theparticle database 1010 and send it to the particle data processing unit1009.

[0088] When the particle data processing unit 1009 finishes reading ofthe data, the analysis screen is displayed as shown in FIG. 19. Threeoperation icons 1051, 1052, 1053 are provided in the lower-central tothe lower-right portion of the screen. The basic data display column1036 is provided in the lower-left portion of the screen. On the centralportion is output the analysis result. This basic data display column1036 on the screen is identical to the basic data display column 1036 onthe initial screen shown in FIG. 12. These operation icons serve as amode change 1051, a hard-copy 1052, and a finish 1053. The mode changeicon 1051 is used for changing the analysis mode. The hard-copy icon1052 is used for printing the screen displayed on the CRT 1013 or theprinter 1014. The finish icon 1053 is used for finishing the analysisand returning the screen to the initial screen.

[0089] Next, the description will be directed to the analysis withreference to FIG. 20, concerning a particle map.

[0090] With respect to the present embodiment, how particles aredistributed on a wafer is displayed on the basis of the informationmeasured in the particle inspection machine 1.

[0091] The analysis operator has to specify a product name. Further, heor she may specify a process name, a lot number, a wafer number, aninspection date, and an operator name if necessary. By specification,the particle database 1010 sends the information about the particlelocation coordinates and the particle diameters to the memory 1016.

[0092] The output depicts an outer circle 1054 of a wafer and indicatesparticle locations by marks. It may over-depict a border line 1055 ofthe chip at this time. And, three size kinds of particles 1059, 1060,1061 have respective display colors or marks. When the mode change icon1051 is specified, at each specification time, it is possible toselectively represent L-, M-, and S-sized particles. Further, it is alsopossible to concurrently specify more than one wafer and display all ofthe particle distributions on the CRT 1013 in an overlapped manner.

[0093] Next, the description will be directed to the analysis withreference to FIGS. 21 and 22. This is referred to as a particle chipmap. The particle data processing unit 1009 serves to perform a particlechip determining algorithm shown in FIG. 22 for counting the number ofparticles existing on each chip. An analysis operator has to specify aproduct name. And, he or she may specify a process name, a lot number, awafer number, an inspection date, and an operation name if necessary. Bythe specification, the location coordinates are retrieved from theparticle database 1010 and are stored in the memory 1016 (step 10010).Then, the stored wafer number J is counted (step 10011). And, the chiphorizontal width 1020, the chip vertical width 1019 (respectivelydenoted as a and b), the matrix horizontal width 1023, and the matrixvertical width 1022 are read into the particle data processing unit 1009from the map information file saved in the internal harddisk 1017. Theparticle chip determining algorithm will be described later. In thepresent embodiment, the area of a (n, m)th chip will be represented as;

(n−1)a<x<na

(m−1)b<y<mb

[0094] where x and y respectively denote an X coordinate and a Ycoordinate of each particle. The maximum value of (n, m) is (N, M). Foreach particle, n and m are calculated as follows (step 10014);

n=[x/a]+1

m=[y/b]+1

[0095] By the calculation, it is possible to find a chip to which theparticles belong. Then, a two-dimensional exponent (n, m) is added todenote the position of each particle. Herein, [z] represents a maximuminteger which does not exceed a real number z. For each chip, theparticle number is counted (step 10015) for deriving a particle densityof each chip per wafer (step 10016). How particles exist on each chip isrepresented on the CRT 1013 by changing a chip color or meshing a chipaccording to each number of particles as shown in FIG. 21 (step 10017).

[0096] In addition, in FIG. 21, 1062 to 1065 represent the particlenumber sections per chip.

[0097] Next, the description will be directed to how to assist theanalysis. This is referred to as the optional division of a wafer.

[0098] In the present embodiment, the particle data analysis station 2serves to divide a wafer to be analyzed on the CRT 1013.

[0099] By specifying a product name, it is possible to display a waferimage on which the specified product chips are located on the CRT 1013in a format shown in FIG. 23. And, an analysis operator specifies one ofthe area columns 1066 to 1069 on the screen by moving an arrow mark 1070with the mouse 1012 and then specifies the chip by moving the arrow mark1070 in order to separate the chips according to each particle density.Once one area of the area columns 1066 to 1069 is specified, thesubsequently-specified chips are specified as the area. Each chip isdivided by the color or the mesh according to each area. One example ofthe divided chips is shown in FIG. 24. The divided pattern is recordedas an optional divisional file shown in FIG. 25 in the harddisk 1017included in the particle data analysis station 2. This recording is doneaccording to each product.

[0100] Next, the description will be directed to the analysis withreference to FIG. 26, which relates to wafer division.

[0101] The present embodiment is designed to divide a wafer into severalareas and to calculate and output a particle density of each area.

[0102] In this regard, an analysis operator has to specify a productname and may specify a process name, a lot number, a wafer number, aninspection date, and an operator name if necessary. By thespecification, it is possible to save the particle location coordinates5014, 5015 and the particle size 5016 as shown in FIG. 5C in theinternal memory 1016 from the particle database 1010. And, the analysisoperator specifies a divisional pattern of a wafer. The divisionalpattern can be categorized as a formal divisional pattern, such as adouble circle 1083, a triple circle 1082, and a crossed pattern 1084, asshown in FIG. 27, and a pattern created by the wafer optional divisionspecification as described previously. The double circle and the triplecircle are respectively created by equally dividing a radius of thewafer regarded as a circle into two or three parts. The crossed divisionis created by dividing the wafer by the perpendicular bisector of theorientation flat 2000 and a perpendicular passed through the center ofthe wafer.

[0103] The particle data processing unit 1009 derives a particle densityof each area from the information about the particle locationcoordinates and the wafer area division and outputs the result in agraphical format. In the graph shown in FIG. 26, the ordinate 1071denotes a particle density (number/cm²) and the abscissa 1072 denotesthree areas 1073, 1074, 1075 of the triple circle 1082. For obtainingquantitative data, it is possible to represent precise values (d₁) 1079,(d₂) 1080, and (d₃) 1081 at the top of each bar graph. The bar graph maybe divided according to the particle sizes S 1076, M 1077, and L 1078 sothat the divided sections may have respective colors or meshes. Byspecifying the mode change icon 1051, each divisional pattern for theanalysis can be selected.

[0104] Next, the description will be directed to the analysis withreference to FIG. 28, relating to particle number frequencydistribution.

[0105] The present embodiment is designed to represent the frequencydistribution of the number of particles existing on one wafer.

[0106] An analysis operator has to specify a product name and a processname and may specify an inspection date, a lot number, and a wafernumber if necessary. By the specification, it is possible to save theparticle number 5010 shown in FIG. 5B in the external memory 1016 fromthe particle database 1010.

[0107] The particle data processing unit 1009 serves to derive thenumber of wafers for each range of the specified particle number andoutput on the screen the result as a histogram. In this graph, theabscissa 1085 denotes the particle number, the maximum value and thedivisional range which the analysis operator specifies. The ordinate1086 denotes the number of wafers.

[0108] Next, the description will be directed to an analysis relating toa particle trend chart.

[0109] The present embodiment is designed to output how the particlenumber is changed on time in the process specified by an analysisoperator in a graphical manner.

[0110] The analysis operator has to specify a product name and a processname and may specify a wafer number, a lot number, an inspection date,and an operator name if necessary. By the specification, it is possibleto save the inspection time 5006, the particle number 5010, and theparticle size 5016 as shown in FIGS. 5A, 5B and 5C in the memory 1016from the particle database 1010.

[0111] The particle data processing unit 1009 serves to sort theinformation on time series and output the result in a graphical format.In the graph, the abscissa 1087 denotes a time and the ordinate denotesthe particle number. As a unit for the abscissa 1087, it is possible toemploy any one of a wafer unit, a lot unit, a date unit, a week unit,and a month unit. In case of a wafer unit, as shown in FIG. 29, theparticle data processing unit 1009 outputs a polygon for each of theparticle sizes 1090 to 1092. In the polygon, 1089 denotes a totalnumber. In case of a lot unit, a day unit, a week unit, and a monthunit, it outputs particle frequency distribution 1204 for each unit in agraphical format shown in FIG. 30. In this graphical manner, it servesto calculate an average value 1205 for each unit and output the resulton the frequency distribution 1204 in a polygon manner. The abscissa isallowed to be horizontally scrolled by specifying a right or left halfpart of the graph with the mouse 1012 if it is impossible to display theinformation being processed on the screen. The ordinate denotes a rangeto be selectively specified by the mode change icon 1051.

[0112] Next, the description will be directed to an inter-processparticle trend with reference to FIG. 31.

[0113] The present embodiment is designed to output the particle trendon a wafer between processes in a polygon manner on the basis of theinformation measured n each process by the particle inspection machine1.

[0114] By specifying more than one process name, it is possible toretrieve the information about the number of all particles 5010 for eachwafer, the particle size 5016, and the inspection date and time 5005,5006 from the particle database 1010 and save the retrieved informationin the internal memory 1016.

[0115] The particle data processing unit 1009 serves to count the numberof particles for each particle size, sort the process names in theinspection order given when the process name is specified, and outputthe particle number on the CRT 1013 as a polygon. In the polygon, it ispossible to change lines and dots for each of the particle sizes (1092to 1094) for displaying these size kinds of particles at the time of orseparately from the number of all particles (1091). The abscissa 1089denotes the sequence of processes (inspection time series) and has fixedintervals. The ordinate denotes an average particle number per wafer. Ifthere exist so many specified processes that all of them are notdisplayed on the screen, it is possible to scroll the axis horizontallywith the method described previously with respect to the analysis ofparticle trend.

[0116] Next, the description will be directed to particle hysteresiswith reference to FIG. 32.

[0117] The present embodiment is designed to output how the particlesare attached or removed in each process in a graphical manner.

[0118] An analysis operator has to specify a product name, more than oneprocess name, and a lot number and may specify a wafer number ifnecessary. By the specification, it is possible to save the particlelocation coordinates 5014, 5015 on the specified wafer, the inspectiondate 5005, and the inspection time 5006 as shown in FIG. 5 in the memory1016 from the particle database 1010.

[0119] In the particle data processing unit 1009, the particle tracealgorithm to be described later clearly indicates how the particles areattached or removed in each process. The particle trace algorithm willbe described in FIG. 33. At first, the algorithm sorts the specifiedprocess names in earlier order by referencing the inspection date 5005and the inspection time 5006 (step 10018). Then, it creates a sensedparticle list for each process (step 10019) and then makes the causedparticle list in the initial process identical to the sensed particlelist therein (step 10020). The format of the sensed particle list isequal to that of the caused particle list, which is shown in FIG. 34.Next, the algorithm calculates a distance between the particle locationcoordinates on the wafer in the initial process and the particlelocation coordinates on the same wafer in the next process in therecording order of the coordinate data. If a calculated distance issmaller than a predetermined constant value R, these two particles aboutthe distance are specified as the same. Then, the similar calculation isdone about the next particle. If no particles in the second process arefound to be equal to the particles sensed in the initial process, it isdetermined that the particles are removed. If no particles sensed in aprocess are found to be equal to the particles sensed in the previousprocess, it is determined that the particles are newly attached in theprocess. The particles to be newly attached in the new process areregistered in the particle occurrence list in the new process (step10021). The similar calculation is done in the order of the earlierprocesses.

[0120] As shown in FIG. 32, the particle data processing unit 1009serves to output a bar chart in which the ordinate 1096 denotes aparticle number and the abscissa 1095 denotes a process name. Theprocess name is ranged from the left side in the earlier order. In thebar chart, the attached particles are separated in a layered manner ineach process A, B or C (three layers 1100, 1101, 1102 shown in FIG. 32).These layers are respectively represented by colors and meshes and theline is drawn between the upper and the lower lines of one layer andthose of another layer. If two or more wafers are specified, the processtracing is done for each wafer. What is displayed on one screen is anaverage value of these wafers.

[0121] Next, the description will be directed to a process unit particlemap.

[0122] The present embodiment is designed to extract only the particlesattached on the wafer in the same process on the basis of theinformation measured by the particle inspection machine 1 in eachprocess and then output the result as a particle map shown in FIG. 20.

[0123] An analysis operator has to specify a product name, two or moreprocess names, and a lot number and may specify a wafer number ifnecessary. By the specification, the location coordinates 5014, 5015,the inspection date and time 5005, 5006, and the process name are savedin the internal memory 1016 from the database 1010.

[0124] The particle data processing unit 1009 serves to create theparticle occurrence list in each process using the particle tracealgorithm described previously. After finishing the procedure, theprocess unit particle map is displayed in the inspection process order.For displaying the next step, it is necessary to specify the mode changeicon 1051.

[0125] With reference to FIG. 35, the visual inspection machine 4 andthe defects data analysis station 5 in the inspection data analysissystem mentioned with reference to FIG. 1 are detailed. The presentsystem comprises the visual inspection machine 4 and the defects dataanalysis station 5 for analyzing the data supplied from the visualinspection machine 4. The visual inspection machine is connected to thedefects data analysis station 5 through the communication line 6.

[0126]FIG. 36 illustrates the arrangement of the visual inspectionmachine 4, which comprises a defects sensing section 1103 for sensingparticles and pattern defects generally referred to as defects, adefects sensing signal processing unit 1104, a memory 1206, a keyboard1105, a bar-code reader 1106, both of which serve as input units, a CRT1107, a printer 1108, both of which serve as output units, and anexternal communication section 1109 which serve to communicate with thedefects data analysis station 5. The visual inspection machine 4provides functions of recognizing two-dimensional coordinates, sizes,and kinds of the visual sensed defects on a wafer and counting thenumber of defects on the wafer, the number of critical defects, thenumber of critical defects in the inspected process, the number of chipswith defects, the number of chips with critical defects, the number ofchips with critical defects in the process, and the number of inspectionchips. The kind and critical level of the defects are determined by theanalysis operator observing a defects image displayed on the CRT 1107.And, if the analysis operator determines that the observed defects arecritical and caused in the inspected process, these defects arecategorized as the critical defects in the inspected process.

[0127]FIG. 37 illustrates the arrangement of the defects data analysisstation 5, which comprises a defects data processing unit 1110, adefects database 1111, a keyboard 1112, a mouse 1113, both of whichserve as input units, a CRT 1114, a printer 1115, both of which serve asoutput units, an external communication section 1116 serving tocommunicate with the visual inspection machine 4, a floppy disk drive1117, a memory 1118 contained in the defects data processing unit, aharddisk 1119, and a CPU 1120.

[0128] The visual inspection machine 4 receives the defects managementdata such as a type of a wafer to be inspected, a process name to beinspected, a lot number, a wafer number, an inspection data and time,and an operator name, which are inputted by the keyboard 1105 or thebar-code reader 1106. The memory 1206 serves to save both of the defectsinspection data and the defects management data. The defects inspectiondata contains the number of defects on an inspected wafer, the number ofcritical defects, the number of critical defects in the inspectedprocess, the number of chips with defects, the number of chips withcritical defects, the number of chips with critical defects in theinspected process, the location coordinates of defects inside of theinspected chip, and the type and the critical level of the defects.

[0129] The arrangement of the defects database 1111 will be describedwith reference to FIG. 38. The basic arrangement is the same as that ofthe particle database 1010 described previously.

[0130] The particle defects data processing unit 1110 includes a productunit wafer number management file shown in FIG. 39, the map informationfile described previously, and the harddisk 1119.

[0131] Next, the flow of data will be described in the present system.After the visual inspection machine 4 finishes the inspection of onewafer, it sends the defects management data and the defects inspectiondata to the defects data analysis station 5 through the communicationline 6. The subsequent flow is substantially same as the flow of datadescribed in the embodiment 2, except that the processing data is thedefects management data and the defects inspection data and is processedon a wafer unit.

[0132] A description of how to use the defects data analysis station 5will be provided. It is generally the same as the description about howto use the particle data analysis station 2. The different respect isthat the basic data column 1036 displays the number of critical defects,a fraction defective, and a defect density in place of the number ofl-sized particles, the number of M-sized particles, and the number ofS-sized particles and the analysis function icon indicates analysisfunctions described previously.

[0133] Next, the description will be directed to an analysis relating toa defect map.

[0134] This operation is generally the same as that designed to analyzeparticles using the particle inspection system, while the presentoperation is designed to analyze defects using the visual inspectionsystem described previously. In the output form, the particle sizes havebeen represented by the colors or marks on the dots, while the presentembodiment represents the categories of defects by the colors or marks.

[0135] Next, the description will be directed to the analysis relatingto a defect chip map.

[0136] The present operation is generally the same as that designed toanalyze particles using the particle inspection system, while thepresent operation is designed to analyze defects using the visualinspection system.

[0137] Next, the description will be directed to analysis relating towafer division.

[0138] The present operation is generally the same as that designed toanalyze particles using the particle inspection system, while thepresent operation is designed to analyze the defects using the visualinspection system.

[0139] Next, the description will be directed to analysis relating todefect number frequency distribution.

[0140] The present operation is generally the same as that designed toanalyze the particles using the particle inspection system, while thepresent operation is designed to analyze the defects using the visualinspection system.

[0141] Next, the description will be directed to an analysis of defecttrend.

[0142] The present operation is generally the same as that designed toanalyze the particles using the particle inspection system, while thepresent operation is designed to analyze the defects using the visualinspection system. In the output form, the particle sizes have beenrepresented by the colors or marks on the polygonal lines and dots,while the present operation represents the categories of defects bythem.

[0143] Next, the description will be directed to an analysis ofinter-process defect trend.

[0144] The present operation is generally the same as that designed toanalyze the particles using the particle inspection system, while thepresent operation is designed to analyze the defects using the visualinspection system. In the output format, the arrangement discussedregarding FIG. 29 represents particle sizes, while the present operationrepresents the categories of the defects, by the colors or marks on thepolygon lines and the dots, respectively.

[0145] Next, the description will be directed to analysis of defecthysteresis.

[0146] The present operation is generally the same as that designed toanalyze the particles using the particle inspection system, while thepresent operation is designed to analyze the defects using the visualinspection system.

[0147] Next, the description will be directed to the analysis withreference to FIG. 40. This operation is referred to as chip fractiondefective trend. An analysis operator has to specify a product name, aprocess name, and an inspection date and may specify a lot number ifnecessary. By the specification, it is possible to save a lot number inthe specified lot, a wafer number, a visual defect chip number 5045, acritical defect chip number 5044, an inspection chip number, aninspection time 5039 in the memory 1118 from the defects database 1111.The defect data processing unit serves to calculate the chip fractiondefective and the critical chip fraction defective on the basis of theforegoing data in accordance with the following equations;

chip fraction defective=defects chip number/inspected chip number×100

critical chip fraction defective=critical defects chip number/inspectedchip number×100

[0148] The data about each wafer is sorted in time sequence order on thebasis of the inspection date 5038 and the inspection time 5039.

[0149] On the CRT 1114 as an output form, the trends of the chipfraction defective 1112 and the critical chip fraction defective 1122are displayed as polygons having respective colors or polygon types. Inthe polygon, the left-hand ordinate 1124 denotes the chip fractiondefective, the right-hand ordinate 1125 denotes the critical chipfraction defective, and the abscissa denotes the lot number and wafernumber, which are displayed in the earlier order from the left hand.

[0150] Next, the description will be directed to analysis relating tochip defect density trend. An analysis operator has to specify a productname, a process name, and an inspection date and may specify a lotnumber if necessary. By the specification, it is possible to save a lotnumber and a wafer number in the inspected lot, a defects number 5043,an inspected chip number, and an inspection time 5039 in internal memory1118 from the defects database 1111. The defects data processing unit1110 serves to calculate a chip defects density and a critical chipdefects density on the basis of the saved data in accordance with thefollowing equations;

chip defects density=critical defects number/inspected chip number×100

critical chip defects density critical defects number/inspected chipnumber×100

[0151] And, the data about each wafer is sorted in time sequence orderon the basis of the inspection date 5038 and the inspection time 5039.

[0152] On the CRT 1114 as an output form, the trends about the chipdefects density and the critical chip defects density are displayed bypolygons 1126 and 1127 having respective colors or polygon types. Thelefthand ordinate 1128 denotes a chip defects density, the right-handordinate 1129 denotes a critical chip defects density, and the abscissadenotes a lot number and a wafer number, which are displayed in earlierorder from the left hand side of FIG. 41.

[0153] Next, the description will be directed to an analysis referred toas a process unit fraction defective.

[0154] An analysis operator has to specify a product name and two ormore process names and may specify a lot number, a wafer number, and aninspection date if necessary. By the specification, it is possible tosave the corresponding lot and wafer numbers, a defective chip sum, acritical defective chip sum, a critical defective chip sum and aninspected chip number in the inspected process, an inspection date, andan inspection time in the internal memory 1118 from the defects database1111. On the basis of the data, the defects data processing unit servesto calculate a total fraction defective 1131, a critical fractiondefective 1132, and an inspected-process critical fraction defective1133 in accordance with the following equations.

total fraction defective=defective chip sum/inspected chip sum×100

critical fraction defective=critical defective chip sum/inspected chipsum×100

inspected-process fraction defective=inspected-process criticaldefective chip sum/inspected chip sum×100

[0155] wherein if there exists data about two or more wafers in aprocess, the data is averaged about the wafers. The product names aresorted in earlier order on the basis of the inspection date 5038 and theinspection time 5039.

[0156] On the CRT 1114 as an output form, it is possible to display, ineach process, the total fraction defective 1131, the critical fractiondefective 1132, and the inspected-process critical fraction defective1133 using polygons. In the polygons, the abscissa 1139 denotes theprocesses, which are ranged in earlier order and the ordinate 1140denotes the fraction defectives having respective colors and meshes.

[0157] Next, the description will be directed to an analysis method of aprocess unit fraction defective with reference to FIG. 43. An analysisoperator has to specify a product name and two or more process names andmay specify a lot number, a wafer number, and an inspection date ifnecessary. By the specification, it is possible to save thecorresponding lot and wafer numbers, a pattern defect chip number, aparticle-defect chip number, the other type defect chip number, aninspected chip number, an inspection date, and an inspection time in theinternal memory 1118 from the defects database 1111. On the basis of thedata, the defects data processing unit serves to calculate a fractiondefective of the pattern-defect chip, a fraction defective of theparticle-defect chip, and a fraction defective of the other type-defectchip in accordance with the following equations;

fraction defective of the pattern-defect chip=pattern-defect chipnumber/inspected chip number×100

fraction defective of the particle-defect chip=particle-defect chipnumber/inspected chip number×100

fraction defective of the other type-defect chip=the other type-defectchip number/inspected chip number×100

[0158] wherein if there exists data about two or more wafers in aprocess, the data is averaged about the wafers. The process names areranged in time sequence order on the basis of the inspection date andthe inspection time.

[0159] On the CRT 1114 as an output form, it is possible to display, foreach process, the pattern-defect chip fraction defective 1143, theparticle-defect chip fraction defective 1142, and the other type-defectchip fraction defective 1141 using polygons 1148, 1147, 1146. In thepolygons, the axis of abscissa 1143 denotes the processes, which arearranged in time sequence order from the left hand side of FIG. 43, andthe ordinate denotes the pattern fractions defective having respectivecolors or meshes.

[0160] An embodiment having the particle inspection machine 1, theparticle data analysis station 2, the probing tester 7, and the probingtest data analysis station 8 is illustrated in FIG. 44.

[0161]FIG. 45 illustrates the arrangement of the probing tester 7, whichcomprises a probing test unit 1146, a probing data inspection andprocessing unit 1147, a keyboard 1148, a bar-code reader 1149, both ofwhich are served as an input unit, a CRT 1150, a printer 1151, both ofwhich are served as an output unit, an external communication unit 1152for communicating with the probing test data analysis station 8, and amemory 1207 contained in the data processing unit 1147. This probingtester 7 serves to test a product character of semiconductor devicesintegrated on a wafer.

[0162]FIG. 46 illustrates the arrangement of the probing test dataanalysis station 8, which comprises a probing data processing unit 1153,a probing database 1154 for saving the result supplied by the probingdata processing unit 1153, a keyboard 1155, a mouse 1156, both of whichare served as an input unit, a CRT 1157, a printer 1158, both of whichare served as an output unit, a first external communication unit 1159for communicating with the probing tester 7, a second externalcommunication unit 1160 for communicating with the particle dataanalysis station 2, a memory 1161, a harddisk 1162, and a CPU 1163. Thearrangement of the particle data analysis station 2 shown in FIG. 44 isgenerally same as that shown in FIG. 4, except that it additionallyprovides an external communication unit 1164 for communicating with theprobing data inspection analysis station 8 (see FIG. 47).

[0163] When the wafer is inspected, the probing tester 7 receivesprobing management data input by the keyboard 1148 or the bar-codereader 1149. The probing management data contains a type of theinspected wafer, a lot number, a wafer number, an inspection date andtime, and an operator name. The probing tester 7 serves to test anelectric characteristic of a chip on the inspected wafer and save theprobing test data consisting of the inspected result and the location ofthe chip together with the probing management data. The coordinatesystem shown in FIG. 6 is used for showing the location of the chip.When the probing tester 7 finishes the inspection of one slot, theprobing test data analysis station 8 reads the probing management dataand the probing test data of the inspected lot from the probing tester7. Then, it serves to determine if the product is defective on the basisof the probing test data and register the result in the probing database1154 as shown in FIG. 48. The probing database 1154 includes two datatables, that is, a probing test lot data table (see FIG. 48A) for theprobing management data 1146 to 1150 except the wafer number and aprobing test wafer data table (see FIG. 48B) for the lot number 1151,the wafer number 1150, and the probing test data 1153 to 1156.

[0164] The arrangement of the particle database 1010 is same as thatdescribed previously.

[0165] The particle data processing unit 1009 includes an analysis dataauxiliary file shown in FIG. 49, a map information file describedpreviously, and a product unit lot number management file. The analysisdata auxiliary file contains the estimated product number 1158 per waferregistered in each product. The function of the product unit lot numbermanagement file is generally same as that described previously, exceptthat when the product unit lot number becomes zero, the data about theproduct is deleted from the analysis auxiliary file.

[0166] The way to use the particle data analysis station 2 is generallythe same as that previously described, except for additional analysisfunctions which are described hereinafter.

[0167] Next, the description will be directed to correlation analysisrelating to a particle yield with reference to FIG. 50.

[0168] The present operation serves to output as a correlation chart therelation between the particle number existing on a wafer being processedand a probing test yield given after the wafer processing process isover. The algorithm for the data analysis is illustrated in FIG. 51.

[0169] An analysis operator specifies a product name and a lot number(step 10022). By the specification, it is possible to save the wafernumber of the specified lot and the particle number of each wafer in theinternal memory 1118 from the particle database 1010 (step 10023) andyields of wafers in the specified lot in the memory 1118 from theprobing data test station 8 (step 1024). The particle data processingunit 1009 serves to match the particle number to the wafer yieldaccording to the wafer number (step 10025) and create the correlationchart (step 10026). As an output format, the abscissa 1165 denotes theparticle number and the ordinate 1166 denotes the yield represented by apercent unit. Several dots 1167 are provided for calculating a primaryregression line 1158 and depicting it on the chart.

[0170] Next, the description will be directed to an analysis withreference to FIG. 52, which is referred to as particle yield overlaytrend.

[0171] The present operation is designed to output as polygons a trendabout the number of particle existing on a wafer being manufactured anda trend about a probing test yield of the manufactured wafer.

[0172] An analysis operator has to specify a product name and aninspection period and may specify a lot number if necessary. By thespecification, it is possible to save an inspection date 5005, aninspection time 5006, a wafer number 5009, and a particle number 5010 ofthe lot matching to a retrieval condition shown in FIG. 5 in theinternal memory 1118 from the particle database 1010 and the probingdata of the wafer in the internal memory 1118 from the probing test dataanalysis station 8. The particle data processing unit 1009 serves tosort the wafers in earlier order on the basis of the inspection date andtime. As an output format, the abscissa 1175 denotes the wafer numbers,which are ranged from the left. The righthand ordinate 1169 denotes aparticle number and the left-hand ordinate 1170 denotes a wafer yield.The dots 1171 indicating the number of particles existing on the samewafer and the dots 1172 indicating yields are given on the same verticalaxis so that both of those dots are connected for creating two polygons1173, 1174. Two polygons have respective colors or kinds of polygons.

[0173] Next, the description will be directed to an analysis withreference to FIG. 53 which is referred to as a yield for each particlesize.

[0174] The present operation is designed to output as a bar-chart therelation between a particle size on a wafer being manufactured and aprobing test yield of the manufactured wafer.

[0175] An analysis operator has to specify a product name, a processname, and a lot number. By the specification, it is possible to save awafer number in the specified lot, particle location coordinates 5014,5015 on each wafer, and a particle size 5016 in the internal memory fromthe particle database 1010 and a wafer number in the specified lot and adetermined result, good or defective, of each chip existing on the waferfrom the probing test data station 8. The particle size is categorizedinto three classes of L, M, and S in order as described previously.

[0176] The particle data processing unit 1009 serves to determine theparticle chips existing on each wafer and record their particle sizes onthe basis of the chip arrangement information and the particle locationcoordinates. For doing so, the particle data processing unit 1009employs the particle chip determining algorithm as described previously.For recording the particle size, if two or more particles exist on onechip, the largest particle size is representatively used. The chips arecategorized into four classes of L-, M-, and S-sized particle chips andno particle chips. For each class, a yield is derived. In the presentembodiment, the yield is defined for each particle size by the followingequation:

yield for particle size=the number of goods in a particle chip for eachparticle size/the number of particle chips for each particle size×100

[0177] On the CRT 1013 as an output form, the abscissa 1176 denotes theparticle sizes, which are ranged from no particles, S-sized particles,M-sized particles, and L-sized particles from the left. The ordinate1177 denotes a yield for each particle size, which is displayed on eachparticle size denoted by the axis of abscissa of the bar chart.

[0178] Next, the description will be directed to an analysis withreference to FIG. 54 which is referred to as a fraction defective ineach process in which particles are attached on a wafer (referred to asa particle process). The present operation is designed to output aprobing test yield of the manufactured wafer in each particle process asa bar chart form.

[0179] An analysis operator has to specify a product name, two or moreprocess names, and a lot number. By the specification, it is possible tosave the inspection date 5005 and the inspection time 5006 as shown inFIG. 5, a wafer number 5013 of the lot, and particle locationcoordinates 5014, 5015 on each wafer in the internal memory from theparticle database 1010 and the wafer number of the lot and thedetermined result, good or defective, of each chip in the wafer in theinternal memory from the probing test data analysis station 8.

[0180] The particle data processing unit 1009 serves to create aparticle extracting map for each process as described previously. Forthe particle extracting map for each process, the particle-attached chipdetermining algorithm is used for determining if the particles areattached on each chip. The unit 1009 serves to-count the number of theparticle-attached chips for each process and the number of good chipsexisting in the number of particle-attached chips. The output isdisplayed in the CRT 1013, in which the abscissa 1184 denotes theprocess names ranged in earlier order from the left and the ordinate1185 denotes the chip number. For each process A, B, or C, the bar chartindicating the number of the particle-attached chips is created. The barchart is categorized into two layers in which the lower layer denotesthe number of good chips 1183 contained in the particle-attached chipand the upper layer denotes the number of defective chips 1182 containedtherein. These layers have respective colors and meshes.

[0181] An embodiment which includes the visual inspection machine 4, thedefect data analysis station 5, the probing tester 7, and the probingtest data analysis station 8 in the inspection data analysis system isdescribed with reference to FIG. 55. This embodiment substantiallyemploys the arrangement of the system described in FIG. 44, except thatthe visual inspection machine 4 and the defect data analysis station 5are employed in place of the particle inspection machine 1 and theparticle data analysis station 2. The visual inspection machine 4 isquite identical to the visual inspection machine 4. The defect dataanalysis station 5 includes the arrangement of the defect data analysisstation 5 described in FIG. 37 as well as an external communication unit1189 for communicating with the probing data analysis station 8 (seeFIG. 56).

[0182] The data to be inputted in or outputted from the probing tester 7is identical to that described with reference to FIG. 44. The defectdatabase 1111 has the same arrangement of that described in FIG. 38.

[0183] The defect data processing unit 1110 includes the analysis dataauxiliary file shown in FIG. 39, the map information file shown in FIG.7, and the product unit wafer number management file, which is generallysame as that shown in FIG. 8 except that if the product unit wafernumber becomes zero, the data about the product kind is deleted from theanalysis data auxiliary file.

[0184] As to how to use the defect data analysis station 5, it is thesame as how to use the defect data analysis station 5 describedpreviously, except that the content of the analysis function icon has anadditional analysis function.

[0185] Next, the description will be directed to an analysis, which isreferred to as a defect yield correlation analysis.

[0186] The present operation is generally the same as that designed toanalyze the particles using the inspection data analysis systemdescribed previously, while the present embodiment is designed toanalyze the defects using the inspection data analysis system.

[0187] Next, the description will be directed to analysis which isreferred to as visual yield overlay trend.

[0188] This operation is generally the same as that designed to analyzethe particles using the particle probing test system, while the presentoperation is designed to analyze the defects using the visual probingtest system. In FIG. 52, the right-hand ordinate 1169 denotes a defectnumber, the left-hand ordinate 1170 denotes a yield, and the abscissa1175 denotes a lot number and a wafer number.

[0189] Next, the description will be directed to an analysis, which isreferred to as a yield for each kind of defect.

[0190] This operation is generally the same as that designed to analyzethe particles using the particle probing test system, while the presentoperation is designed to analyze the defects using the visual probingtest system. The present embodiment treats the category of defects inplace of the category of a particle size. In the present embodiment, asshown in FIG. 53, the ordinate 1177 denotes a yield, and the abscissa1176 denotes defect kinds, which are ranged in the order of patterndefects, particle defects, and the other defects.

[0191] Next, the description will be directed to an analysis, which isreferred to as a yield for each defective process.

[0192] The present operation is generally the same as that designed toanalyze the particles using the particle probing test system, while thepresent operation is designed to analyze the defects using the visualprobing test system. In the present embodiment, as shown in FIG. 54, theordinate 1185 denotes the chip number and the abscissa 1184 denotes theprocess name.

[0193] As to how to categorize the defects, the defects are categorizedinto a cause of defects, a defects-causing phenomenon, and a kind ofdefects. The cause of defects can be categorized into a resist residue,a fingerprint, a reticle, a pattern defect resulting from an reticleerror, a pattern defect resulting from a resolution error, adiscoloration defect resulting from over oxidation, and the other. Thedefects-causing phenomenon can be categorized into a pattern defectresulting from Al corrosion, a pattern defect resulting from a filledcontact hole, a discoloration defect resulting from a pin hole, and theother. The kind of defects can be categorized into a pattern defect, adiscoloration defect, a flaw, or other types of defects. The defects arecategorized in accordance with the foregoing categories in order toperform the data analysis previously described.

[0194] The subject matter of FIG. 57 concerns a wafer manufacturing lineon which the features previously described are used. This wafermanufacturing line is designed to set particle inspection processesimmediately after the manufacturing process on which the particles areoften caused, the process on which the manufacturing machine isadjusted, and the like. And, it sets a reference for a particle numberper wafer to each particle inspection process. The particle dataanalysis station 2 serves to analyze the particle inspection result inthe manner described previously, monitor the change of the particlenumber on time in each particle inspection process, and pick up theprocess having a higher particle number than the reference particlenumber. By the analysis described previously, the station 2 serves topick up the process on which the sensed particle number is larger thanthat in any other process. After a m-th particle inspection process ispicked up, the station 2 serves to select several manufacturingprocesses around the manufacturing process immediately before the m-thparticle inspection process and set the m-th particle inspection processimmediately after the manufacturing process (see FIG. 57). The defectsdata analysis station 5 serves to analyze the visual inspection resultin the manner described previously.

[0195] The foregoing embodiment relating to FIG. 1 has been designed toindividually provide the particle data analysis station 2 and thedefects data analysis station 5, though, it is possible to integratethem into one workstation. The overall arrangement of FIG. 1 will beillustrated in FIG. 58.

[0196] The arrangement of the component unit is equal to those shown inFIGS. 3, 36, 45, and 46, except that the data analysis station 1190includes an external communication unit 1191 for communicating with thevisual inspection machine 4 and the particle data analysis station 2shown in FIG. 47.

[0197] The present invention may be applied to a magnetic diskproduction line. In the hardware arrangement shown in FIG. 1, thepresent invention employs a disk particle inspection machine in place ofthe particle inspection machine 1, a disk particle analysis station inplace of the particle data analysis station 2, a disk visual inspectionmachine in place of the visual inspection machine 4, a disk defectsanalysis station in place of the defects data analysis station 5, a diskfinished product inspection machine in place of the probing tester 7,and a disk product data analysis station in place of the probing dataanalysis station 8. The function of the inspection machine and the dataanalysis station is same as that described in the foregoing embodiments2 to 37. Then, how to set location coordinates on a magnetic disk isdescribed with reference to FIG. 60. On one part of the inner peripheralportion is attached a mark 1192 in the first magnetic disk manufacturingprocess. Assuming that the line connecting between a disk center 1193and the mark is a reference line 1194, a two-dimensional polarcoordinate system on a magnetic disk is set using the disk center andthe reference line. Using the polar coordinate system, it is possible tocarry out the functions such as the analysis, the operation, and theprocessing as described previously. As an output form, nothingcorresponding to the border 1055 of the semiconductor chip is output.

[0198] The present invention is also applied to a substrate productionline. In the hardware arrangement shown in FIG. 1, the presentembodiment employs a substrate particle inspection machine in place ofthe particle inspection machine 1, a substrate particle analysis stationin place of the particle data analysis station 2, a substrate visualinspection machine in place of the visual inspection machine 4, asubstrate defects analysis station in place of the defects data analysisstation 5, a substrate final inspection machine in place of the probingtester 7, and a substrate data analysis station in place of the probingdata analysis station 8. The functions of the inspection machine and thedata analysis station are basically same as those described previously.The present embodiment employs the steps of setting a minimum squareenclosing a work as shown in FIG. 61, a mark 1197 on the work as areference point, and an X-axis 1195 and a Y-axis 1196.

[0199] Using this coordinate system, this embodiment serves to performthe analysis described previously.

[0200] According to the present invention, it has been described thatthe relation between the defects and the product character isconventionally derived by taking the correlation between the defectdensity and the yield on a wafer basis. Since, however, the data can beanalyzed on a chip basis, the present invention is capable of graspingthe relation between the defects causing condition of each chip and theproduct character of the chip, resulting in enabling new analysis of thedata and elucidating the causal relation between the defects (cause) andthe product character (result). This function contributes to providingeffective decision materials for properly improving yields. Further, byindividually using the particle inspection machine and the visualinspection machine, the inspection speeds of which are different, thisinvention has a new function of determining a process to be visuallyinspected in the mass production line from the particle inspectionresult. In addition, it has an advantage that it is unnecessary to matchthe particle inspection data to the defects inspection data in theoverall process and machines.

[0201] The present invention is designed to formalize the operatingmethod and the data retrieval routine in the analysis station andgeneralize the data analysis method. Hence, it is capable of easilyknowing an abnormality-caused process and the content of theabnormality, so that a person in charge of the manufacturing machine cantake rapid measures for the abnormality.

[0202] The present invention establishes a novel method for analyzingdefects resulting from the product defect. This invention can be appliedto the manufacturing line of a product (for example, a magnetic disk ora substrate) requiring visual inspection and final product inspection ofthe work.

We claim:
 1. An inspection system comprising: a first inspection machineto inspect defects on a work piece; a second inspection machine toinspect electric characteristics of chips of the work piece; and ananalysis unit to process inspection results to be inspected by the firstand second inspection machine and to output processing results; whereinsaid analysis unit has a data processing unit to judge which chips arechips with defects by using the inspection results of the firstinspection machine, and to calculate a rate of good chips with defectsor bad chips with defects by using the inspection results of the secondinspection machine, and to output the calculation result.
 2. Theinspection system according to claim 1, wherein said first inspectionmachine is a visual inspection machine or a particle inspection machine.3. An analysis unit comprising: means for judging that which of aplurality of chips are chips with defects by using defect inspectionresults; means for calculating a rate of good chips with defects or badchips with defects by using electrical characteristics inspectionresults; and means for outputting the calculation result.
 4. Aninspection method using a first inspection machine to inspect defects ona work piece and a second inspection machine to inspect electriccharacteristics of chips of the work piece and an analysis unit toprocess inspection results to be inspected by the first and secondinspection machines and to output processing results comprising: a stepfor judging which chips are chips with defects by using the inspectionresults of the first inspection machine; a step for calculating a rateof good chips with defects or bad chips with defects by using theinspection results of the second inspection machine; and a step foroutputting the calculation result.
 5. The inspection method according toclaim 4, wherein said first inspection machine is a visual inspectionmachine or a particle inspection machine.